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Record W1846138672

An Exception to the Rule? Lone French Nouns in Tunisian Arabic

2015· article· en· W1846138672 on OpenAlexfundno aff
Shana Poplack, Lotfi Sayahi, Nahed Mourad, Nathalie Dion

Bibliographic record

VenueScholarly Commons (University of Pennsylvania) · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic and Sociocultural Studies
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsLinguisticsNounInflectionGrammarComputer scienceHistoryPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Reports on language mixing involving Arabic often qualify that language as resistant to constraints operating on other language pairs. But many fail to situate the purported violations with respect to recipient and donor languages, making it impossible to ascertain whether these are exceptional code-switches or (nonce) borrowings; isolated cases or robust patterns. We address these issues through variationist analysis of Tunisian Arabic/French bilingual discourse. Focusing on conflict sites that reveal which grammar is operative when the other language is accessed, we compare quantitatively the behavior of lone French-origin nouns in Arabic with their counterparts in both donor and recipient languages. Despite a higher order community resistance to morphological inflection of other-language items, results show treatment of French nouns to be consistent with the (variable) grammar of Arabic and different from that of French. Applying the same accountable methodology to the contentious French det+n sequences (“constituent insertions”) shows that most are integrated in the same way as their lone counterparts. These too are treated as (compound) borrowings, largely motivated by the semantic imperative of expressing plurality while eschewing inflection. As borrowings, they do not constitute exceptions to code-switching constraints, confirming that the status of mixed items cannot be determined in isolation; they must be contextualized with respect to the remainder of the bilingual system, including donor, recipient, and other mixed-language elements.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.504
Threshold uncertainty score0.949

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.053
GPT teacher head0.291
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2015
Admission routes1
Has abstractyes

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